R Notebook

# read in age data
age <- read_csv(here::here("raw_data/age_data.csv")) %>% 
  clean_names()

age_by_date <- age %>% 
  mutate(
    year = str_extract(week_ending, "^\\d{4}"),
    monthday = str_extract(week_ending, "\\d{4}$"),
    month = str_extract(monthday, "^\\d{2}"),
    day = str_extract(monthday, "\\d{2}$"),
    date = ymd(str_c(year, month, day)), .after = 1
  )

age_date_clean <- age_by_date %>% 
  filter(!age_group=="All ages")
  

# create plot of admissions by age
ggplotly(age_date_clean %>%
  group_by(date, age_group) %>% 
  summarise(avg_admissions = mean(number_admissions)) %>% 
  ggplot() +
  aes(x = date, y = avg_admissions, colour = age_group) +
  geom_line() +
    labs(title = "Mean Admissions by Age Group",
         x = "Date",
         y = "Mean Admissions",
         colour = "") +
    theme_bw())

`summarise()` has grouped output by 'date'. You can override using the `.groups` argument.